Intelligent classification of fetal Doppler blood velocity waveform abnormalities using wavelet transform and vector quantization algorithm

Author

Izzetoglu, Kurtulus ; Erkmen, Aydan M. ; Beksac, Sinan

Author_Institution

Dept. of Electr. & Electron. Eng., Middle East Tech. Univ., Ankara, Turkey

Volume

1

fYear

1995

fDate

22-25 Oct 1995

Firstpage

724

Abstract

The approach presented in this paper uses the features, represented by wavelet coefficients, that are extracted from the variations of blood velocity waveforms obtained from Doppler ultrasound images of fetal umbilical arteries. The obtained reliable features form the training samples of a classification algorithm to be used in intelligent diagnostic for fetal surveillance

Keywords

Doppler effect; biomedical ultrasonics; diagnostic expert systems; feature extraction; image classification; neural nets; vector quantisation; wavelet transforms; Doppler ultrasound images; blood velocity waveforms; feature extraction; fetal umbilical arteries; intelligent classification; intelligent diagnostics; unsupervised neural network; vector quantisation; wavelet coefficients; Arteries; Artificial neural networks; Biomedical engineering; Blood flow; Data mining; Feature extraction; Frequency; Surveillance; Ultrasonic imaging; Wavelet coefficients;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems, Man and Cybernetics, 1995. Intelligent Systems for the 21st Century., IEEE International Conference on

Conference_Location

Vancouver, BC

Print_ISBN

0-7803-2559-1

Type

conf

DOI

10.1109/ICSMC.1995.537850

Filename

537850